lllyasviel / lllyasviel/ControlNet
Much Worse test result when using gradio_canny2image.py than validation result.
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Description
Hi Thanks for your great work.
I've trained Controlnet using Canny Edge.
After 30 epoch, the validation images in image_log show quite realistic good results.
So I used the model and run gradio_canny2image.py and tried with a lot of different parameter settings like CFG, but it shows always so bad result compared to the validation results.
Is there any difference between validation process or parameter settings and web version?
Please help me~!
Thank you!
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Research direction
Start with gradio_canny2image.py and compare its inference parameters and process with the validation process that produced the image_log results. Reproduce the mismatch using the reported trained Canny Edge model and varied CFG settings. Done means identifying and documenting the validation-versus-web-version difference, or confirming that the issue cannot be reproduced with the available details.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 28/100